COMPMID-748 - Integrating optimized SGEMM for bifrost
This patch introduces a new GEMM capable to improve the mac utilisation
of 10% compared to the GEMM without reshape. However this implementation
is not faster in all cases as we need to take into account the time for
reshaping the matrices. For this reason an heuristic solution to select
the optimal GEMM to use has been added to the function. More information
about the heuristic implementation can be found at COMPMID-852.
With this new patch, GoogleNet, MobileNet, VGG16 and SqueezeNet can
improved the performance of 1.5x.
More information about the performance uplift can be found here:
https://confluence.arm.com/display/MLENG/GEMM+FP32+performance%3A+ACL+18.02
Change-Id: I024563c06b9aed02a211a974e452bae5c233b04c
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/117140
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp b/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp
index 6886f54..241dd85 100644
--- a/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp
+++ b/src/core/CL/kernels/CLGEMMInterleave4x4Kernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -40,17 +40,16 @@
namespace
{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, int mult_interleave4x4_height)
{
+ ARM_COMPUTE_RETURN_ERROR_ON(mult_interleave4x4_height < 1);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::U8, DataType::S8,
DataType::QS16, DataType::U16, DataType::S16, DataType::U32, DataType::S32,
DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
if(output->total_size() != 0)
{
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_interleaved_shape(*input));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_interleaved_shape(*input, mult_interleave4x4_height));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
}
@@ -58,11 +57,11 @@
return Status{};
}
-std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, int mult_interleave4x4_height)
{
- unsigned int num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(input->data_type());
+ constexpr unsigned int num_elems_processed_per_iteration_x = 4;
constexpr unsigned int num_elems_processed_per_iteration_y = 4;
- const unsigned int num_elems_written_per_iteration = num_elems_processed_per_iteration_x * num_elems_processed_per_iteration_y;
+ const unsigned int num_elems_written_per_iteration = num_elems_processed_per_iteration_x * num_elems_processed_per_iteration_y * mult_interleave4x4_height;
bool window_changed = false;
// Configure kernel window
@@ -73,7 +72,10 @@
// Configure window in case of configured output
if(output->total_size() != 0)
{
- AccessWindowRectangle output_access(output, 0, 0, num_elems_written_per_iteration, 1, 4.f, 0.25f);
+ const float scale_x = 4.0f * static_cast<float>(mult_interleave4x4_height);
+ const float scale_y = 1.0f / (scale_x);
+
+ AccessWindowRectangle output_access(output, 0, 0, num_elems_written_per_iteration, 1, scale_x, scale_y);
window_changed = window_changed || update_window_and_padding(win, output_access);
output_access.set_valid_region(win, input->valid_region());
}
@@ -88,25 +90,42 @@
{
}
-void CLGEMMInterleave4x4Kernel::configure(const ICLTensor *input, ICLTensor *output)
+void CLGEMMInterleave4x4Kernel::configure(const ICLTensor *input, ICLTensor *output, int mult_interleave4x4_height)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Output auto inizialitation if not yet initialized
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_interleaved_shape(*input->info())));
+ auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_interleaved_shape(*input->info(), mult_interleave4x4_height)));
// Perform validate step
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mult_interleave4x4_height));
_input = input;
_output = output;
+ // Create build options
+ CLBuildOptions build_opts;
+ build_opts.add_option("-DMULT_INTERLEAVE4X4_HEIGHT=" + support::cpp11::to_string(mult_interleave4x4_height));
+ switch(input->info()->element_size())
+ {
+ case 1:
+ build_opts.add_option("-DDATA_TYPE=uchar");
+ break;
+ case 2:
+ build_opts.add_option("-DDATA_TYPE=ushort");
+ break;
+ case 4:
+ build_opts.add_option("-DDATA_TYPE=uint");
+ break;
+ default:
+ ARM_COMPUTE_ERROR("Data type not supported");
+ }
+
// Create kernel
- std::string kernel_name = "gemm_interleave4x4_" + support::cpp11::to_string(input->info()->element_size() * 8) + "bit";
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_interleave4x4", build_opts.options()));
// Configure kernel window
- auto win_config = validate_and_configure_window(input->info(), output->info());
+ auto win_config = validate_and_configure_window(input->info(), output->info(), mult_interleave4x4_height);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure(win_config.second);
@@ -119,10 +138,10 @@
_config_id += support::cpp11::to_string(output->info()->dimension(1));
}
-Status CLGEMMInterleave4x4Kernel::validate(const ITensorInfo *input, const ITensorInfo *output)
+Status CLGEMMInterleave4x4Kernel::validate(const ITensorInfo *input, const ITensorInfo *output, int mult_interleave4x4_height)
{
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mult_interleave4x4_height));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), mult_interleave4x4_height).first);
return Status{};
}
@@ -144,10 +163,6 @@
Window in_slice = window.first_slice_window_2D();
Window out_slice = window.first_slice_window_2D();
- // Change x and y steps for the slide of output tensor
- out_slice.scale(Window::DimX, 4.f);
- out_slice.scale(Window::DimY, 0.25f);
-
do
{
unsigned int idx = 0;
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
index 19f38bf..e23feb2 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -36,24 +36,68 @@
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include <set>
#include <string>
using namespace arm_compute;
+using namespace arm_compute::misc::shape_calculator;
namespace
{
using ElementsProcessed = Steps;
-inline Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, bool is_interleaved_transposed)
+inline Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1);
+
if(!is_interleaved_transposed)
{
ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != input1->dimension(1));
+
+ if(output->total_size() != 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(0) != output->dimension(0));
+ ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(1) != output->dimension(1));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, output);
+ }
+ }
+ else
+ {
+ const int m = reshape_info.m();
+ const int n = reshape_info.n();
+ const int k = reshape_info.k();
+ const int mult_transpose1xW_width = reshape_info.mult_transpose1xW_width();
+ const int mult_interleave4x4_height = reshape_info.mult_interleave4x4_height();
+
+ TensorShape tensor_shape0{ input0->tensor_shape() };
+ tensor_shape0.set(0, k);
+ tensor_shape0.set(1, m);
+
+ TensorShape tensor_shape1{ input1->tensor_shape() };
+ tensor_shape1.set(0, n);
+ tensor_shape1.set(1, k);
+
+ const TensorInfo tensor_info0 = input0->clone()->set_tensor_shape(tensor_shape0);
+ const TensorInfo tensor_info1 = input1->clone()->set_tensor_shape(tensor_shape1);
+
+ const TensorInfo tensor_info_reshaped0 = input0->clone()->set_tensor_shape(compute_interleaved_shape(tensor_info0, mult_interleave4x4_height));
+ const TensorInfo tensor_info_reshaped1 = input1->clone()->set_tensor_shape(compute_transpose1xW_with_element_size_shape(tensor_info1, mult_transpose1xW_width));
+
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input0, &tensor_info_reshaped0);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, &tensor_info_reshaped1);
+
+ if(output->total_size() != 0)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) != static_cast<size_t>(n));
+ ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) != static_cast<size_t>(m));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input0, output);
+ }
}
return Status{};
@@ -122,12 +166,19 @@
{
}
-void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha, bool is_interleaved_transposed)
+void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output);
+ // Output tensor auto inizialitation if not yet initialized
+ TensorShape tensor_shape{ input0->info()->tensor_shape() };
+ tensor_shape.set(0, is_interleaved_transposed ? reshape_info.n() : input1->info()->dimension(0));
+ tensor_shape.set(1, is_interleaved_transposed ? reshape_info.m() : input0->info()->dimension(1));
+
+ auto_init_if_empty(*output->info(), input0->info()->clone()->set_tensor_shape(tensor_shape));
+
// Perform validate step
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), is_interleaved_transposed));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), is_interleaved_transposed, reshape_info));
_input0 = input0;
_input1 = input1;
@@ -176,7 +227,13 @@
std::string kernel_name;
if(is_interleaved_transposed)
{
+ const int mult_transpose1xW_width = reshape_info.mult_transpose1xW_width();
+ const int mult_interleave4x4_height = reshape_info.mult_interleave4x4_height();
+
build_opts.add_option("-DCOLS_B=" + support::cpp11::to_string(input1->info()->dimension(0)));
+ build_opts.add_option("-DMULT_TRANSPOSE1XW_WIDTH=" + support::cpp11::to_string(mult_transpose1xW_width));
+ build_opts.add_option("-DMULT_INTERLEAVE4X4_HEIGHT=" + support::cpp11::to_string(mult_interleave4x4_height));
+
if(data_type == DataType::F32)
{
kernel_name = "gemm_mm_interleaved_transposed_f32_" + string_from_target(arch_target);
@@ -230,11 +287,13 @@
_config_id += (is_interleaved_transposed ? support::cpp11::to_string(input1->info()->dimension(0)) : support::cpp11::to_string(input1->info()->dimension(1)));
}
-Status CLGEMMMatrixMultiplyKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, bool is_interleaved_transposed, GPUTarget gpu_target)
+Status CLGEMMMatrixMultiplyKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, bool is_interleaved_transposed,
+ const GEMMReshapeInfo &reshape_info, GPUTarget gpu_target)
{
+ // Note: num_elements_processed will be set in validate_and_configure_window()
ElementsProcessed num_elements_processed{};
ARM_COMPUTE_UNUSED(alpha);
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output, is_interleaved_transposed));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output, is_interleaved_transposed, reshape_info));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(),
input1->clone().get(),
output->clone().get(),
diff --git a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
index 69a545b..63aed6d 100644
--- a/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMTranspose1xWKernel.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -42,8 +42,9 @@
namespace
{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, int mult_transpose1xW_width)
{
+ ARM_COMPUTE_RETURN_ERROR_ON(mult_transpose1xW_width < 1);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QASYMM8, DataType::U8, DataType::S8,
DataType::QS16, DataType::U16, DataType::S16, DataType::U32, DataType::S32,
DataType::F16, DataType::F32);
@@ -51,7 +52,7 @@
if(output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(),
- compute_transpose1xW_with_element_size_shape(*input));
+ compute_transpose1xW_with_element_size_shape(*input, mult_transpose1xW_width));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output);
}
@@ -59,11 +60,11 @@
return Status{};
}
-std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, unsigned int &num_elems_processed_per_iteration)
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, unsigned int &num_elems_processed_per_iteration, int mult_transpose1xW_width)
{
num_elems_processed_per_iteration = 16 / input->element_size();
- const int scale_x = num_elems_processed_per_iteration;
+ const int scale_x = num_elems_processed_per_iteration * mult_transpose1xW_width;
bool window_changed = false;
// Configure kernel window
@@ -90,25 +91,31 @@
}
} // namespace
-void CLGEMMTranspose1xWKernel::configure(const ICLTensor *input, ICLTensor *output)
+void CLGEMMTranspose1xWKernel::configure(const ICLTensor *input, ICLTensor *output, int mult_transpose1xW_width)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Output tensor auto inizialitation if not yet initialized
- auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_transpose1xW_with_element_size_shape(*input->info())));
+ auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_transpose1xW_with_element_size_shape(*input->info(), mult_transpose1xW_width)));
// Perform validate step
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mult_transpose1xW_width));
_input = input;
_output = output;
// Configure kernel window
+ // Note: num_elems_processed_per_iteration will be set in validate_and_configure_window()
unsigned int num_elems_processed_per_iteration = 1;
- auto win_config = validate_and_configure_window(input->info(), output->info(), num_elems_processed_per_iteration);
+ auto win_config = validate_and_configure_window(input->info(), output->info(), num_elems_processed_per_iteration, mult_transpose1xW_width);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure(win_config.second);
+ // Create build options
+ CLBuildOptions build_opts;
+ build_opts.add_option("-DTRANSPOSE_W=" + support::cpp11::to_string(num_elems_processed_per_iteration));
+ build_opts.add_option("-DMULT_TRANSPOSE1XW_WIDTH=" + support::cpp11::to_string(mult_transpose1xW_width));
+
/*
* Following an example of how the transposition1xW works when the input data type is F32
*
@@ -117,18 +124,18 @@
* |a20 a21 a22 a23| = | a00 a01 a02 a03 || a10 a11 a12 a13 || a20 a21 a22 a23 || a30 a31 a32 a33 |
* |a30 a31 a32 a33|
*
- * The output matrix will have the following shape: [ height * W, ceil(width / W) ], where W = (16 / element size of the tensor)
+ * The output matrix will have the following shape: [ height * W, ceil(width / W) ], where W = (16 / element size of the tensor) * mult_transpose1xW_width
*/
// Create kernel
- std::string kernel_name = "gemm_transpose1x" + support::cpp11::to_string(num_elems_processed_per_iteration);
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name));
+ std::string kernel_name = "gemm_transpose1xW";
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
}
-Status CLGEMMTranspose1xWKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
+Status CLGEMMTranspose1xWKernel::validate(const ITensorInfo *input, const ITensorInfo *output, int mult_transpose1xW_width)
{
unsigned int num_elems_processed_per_iteration = 1;
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), num_elems_processed_per_iteration).first);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mult_transpose1xW_width));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), num_elems_processed_per_iteration, mult_transpose1xW_width).first);
return Status{};
}